Real data-driven occupant-behavior optimization for reduced energy consumption and improved comfort

2021 ◽  
Vol 302 ◽  
pp. 117276
Author(s):  
Kadir Amasyali ◽  
Nora M. El-Gohary
Keyword(s):  
Energy Consumption ◽  
Real Data ◽  
Data Driven ◽  
Occupant Behavior

The impacts of occupant behavior on building energy consumption: A review

2021 ◽  
Vol 45 ◽  
pp. 101212
Author(s):  
Shuo Chen ◽  
Guomin Zhang ◽  
Xiaobo Xia ◽  
Yixing Chen ◽  
Sujeeva Setunge ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Building Energy ◽  
Occupant Behavior ◽  
Building Energy Consumption

Operation Optimization Approaches of Thermal Power Units with Big Data-Driven Hybrid Modeling

2014 ◽  
Vol 631-632 ◽  
pp. 362-366
Author(s):  
Ning Ling Wang ◽  
Yong Zhang ◽  
Long Fei Zhu ◽  
Zhi Ping Yang
Keyword(s):  
Energy Consumption ◽  
Thermal Power ◽  
Hybrid Modeling ◽  
Data Driven ◽  
Fuzzy Rough Set ◽  
Operation Optimization ◽  
Operation Conditions ◽  
Energy Consumption Model ◽  
Practical Guidelines ◽  
Data Driven Modeling

An accurate and reliable energy-consumption model is the key to operation optimization and energy-saving diagnosis of thermal power units especially under different operation conditions and boundaries. Conventional mathematical and data-driven modeling methods were overviewed and compared in this paper. A hybrid modeling based on thermodynamic theory and fuzzy rough set (FRS) method was proposed to process the great volume of operation data and describe the energy-consumption behavior of thermal power units. On this basis, the operation optimization was performed with intelligent computation methods to derive the realizable benchmark state with the whole set of operation parameters. The resultant optimum operation state reflects the exterior factors and system behavior, taking practical guidelines for the modeling and optimization of large thermal power units.

Thermal performance assessment of cool roofs on supermarkets through case analysis in 13 cities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Juan Carlos Ríos-Fernández
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Energy Savings ◽  
Real Data ◽  
Research Approach ◽  
Environmental Implications ◽  
Content Type ◽  
Cool Roof ◽  
Increase Energy Efficiency ◽  
Cool Roofs

PurposeThis paper aims to study the use of cool roof technology to avoid unnecessary energy consumption in supermarkets. This will allow to reduce and even cancel the heat absorbed by the roofs, transferring it to the buildings and thus, creating more sustainable cities.Design/methodology/approachThirteen real supermarkets with cool roofs were analysed in Australia, Canada, the USA and Spain. An analysis of so many supermarkets located in different parts of the world with different climatic zones has allowed an inductive analysis, obtaining real data of energy consumption associated with the air conditioning installations for a year with and without implementing the cool roof technology.FindingsThe paper provides insights on how the use of cool roof managed to reduce the need for energy for heating, ventilating and air conditioning by between 3.5 and 38%. Additionally, this technology reduces the annual generation of carbon dioxide (CO2) emissions per square meter of supermarket up to 2.7 kgCO2/m2. It could be an economical technology to apply in new and old buildings with a period of average economic recovery of four years.Research limitations/implicationsBecause of the chosen research approach, the research results may be generalisable. Therefore, researchers are encouraged to test proposals in construction with other uses.Practical implicationsThe paper includes economic and environmental implications for the development of cool roof technology and smooths the way for its implementation to increase energy efficiency in commercial buildings.Originality/valueThis paper is an innovative contribution to the application of cool roof technology as a source of energy savings in commercial construction through the analysis of supermarkets located in different countries with different climate zones. This will help other researchers to advance in this field and facilitate the implementation of the technology.

scholarly journals Predicting Building Energy Consumption using Engineering and Data Driven Approaches: A Review

2017 ◽  
Vol 2 (5) ◽  
pp. 44 ◽  
Author(s):  
Aulon Shabani ◽  
Orion Zavalani
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Building Energy ◽  
Data Driven ◽  
World Population ◽  
Design Phase ◽  
Energy Prediction ◽  
Important Concern ◽  
Paper Review ◽  
Second Category

Rapid growth of world population has higher impact on increasing buildings energy consumption. Therefore, improving energy consumption is an important concern for building engineers and operators. Energy management through forecasting approaches as one of most effective methods is in focus of this paper. Review of most elaborated methods is in our focus, where we investigate two main directions of energy prediction approaches. First category of approaches focuses on engineering methods mainly very reliable on building early operation stages and design phase, meanwhile second category go through data driven methods. Existing research works focused on these two models are introduced emphasizing advantages and relevant applications of methods.

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